The success of new ventures can hinge on obtaining venture capital (VC) funding. Virtually every successful IT venture has depended on VC funding early in its history. However, obtaining venture capital is difficult. Unlike earlier studies on VC funding that consider new ventures to be homogeneous, this study seeks to identify factors that VCs consider when they make funding decisions for IT ventures. Building on prior research in the area of agency and business risk, we develop a theoretical model that draws on work in finance and entrepreneurship. The model suggests that VCs consider two types of risk: business risk and agency risk. The relative importance of these two types of risk may be different across industries. We test this model using data from 139 business plans for IT startups that were considered for funding by VCs. Traditional structural equation modeling (SEM) does not accommodate non-normal data or dichotomous outcome variables. Using the Robust Weighted Least Squares approach, we test our model with non-normal data and dichotomous outcomes. In addition, we use Tetrad analysis to check model fit against alternative models, floor and ceiling analysis to test sample frame validity, relative effect size comparison to test relative elasticity of effects, and a Monte Carlo estimation approach to test overall model power and power of individual paths. We find that business risk is an important factor in start- up funding for IT ventures. We do not find agency risk to be an important consideration in start-up funding for IT ventures.